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Analysis of the genetic diversity and mRNA expression
level in porcine reproductive and respiratory syndrome
virus vaccinated pigs that developed short or long
viremias after challenge
Martí Cortey, Gaston Arocena, Tahar Ait-Ali, Anna Vidal, Yanli Li, Gerard
Martín-Valls, Alison D. Wilson, Allan L. Archibald, Enric Mateu, Laila
Darwich
To cite this version:
SHORT REPORT
Analysis of the genetic diversity
and mRNA expression level in porcine
reproductive and respiratory syndrome virus
vaccinated pigs that developed short or long
viremias after challenge
Martí Cortey
1*†, Gaston Arocena
1†, Tahar Ait‑Ali
2, Anna Vidal
1, Yanli Li
1, Gerard Martín‑Valls
1, Alison D. Wilson
2,
Allan L. Archibald
2, Enric Mateu
1,3and Laila Darwich
1,3Abstract
Porcine reproductive and respiratory syndrome virus (PRRSv) infection alters the host’s cellular and humoral immune response. Immunity against PRRSv is multigenic and vary between individuals. The aim of the present study was to compare several genes that encode for molecules involved in the immune response between two groups of vacci‑ nated pigs that experienced short or long viremic periods after PRRSv challenge. These analyses include the sequenc‑ ing of four SLA Class I, two Class II allele groups, and CD163, plus the analysis by quantitative realtime qRT‑PCR of the constitutive expression of TLR2, TLR3, TLR4, TLR7, TLR8 and TLR9 mRNA and other molecules in peripheral blood mononuclear cells.
© The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Introduction, methods and results
Introduction
Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically important swine diseases worldwide [1]. Currently, two species of PRRS virus are recognized: PRRSv-1 and PRRSv-2 both within the genus
Porartevirus, Family Arteriviridae. The genome size
of PRRSv is about 15 Kb with at least 10 open reading frames (ORFs). ORF1a and 1b encode for two polypro-teins that after enzymatic cleavage will result in at least 14 non-structural proteins (Nsps) involved in viral rep-lication, plus at least two other proteins encoded after a ribosomal frameshift [2]. The 3′ end of the viral genome (ORFs 2a to 7) encodes five minor (GP2a, GP3, GP4,
ORF5a protein and E) and three major (GP5, M and N) structural proteins [3].
The primary target of PRRSv are CD163+ macrophages
that are common in lungs and lymphoid organs, par-ticularly tonsil [4]. The entry of the virus into target cells involves: (i) an initial attachment to the cell sur-face, probably mediated by heparan sulfate (HS) [5] and porcine sialoadhesin-1 [6]—also known as CD169—or other sialoadhesins [7], probably by interacting with the GP5-M heterodimer, (ii) the internalization of the virus by endocytosis, (iii) the interaction with CD163, driven by the viral GP2-GP3-GP4-E complex, and (iv) the sub-sequent release of the viral genome into the cytoplasm [4]. Of the abovementioned receptors CD163 is consid-ered to be the essential one. Actually, gene-edited pigs lacking the exon 7 of CD163 resulted in the generation of porcine alveolar macrophages (PAMs), and macrophages derived from peripheral blood completely resistant to both PRRSv-1 and 2 [8].
A key feature of PRRSv infection is the alteration of the host’s cellular and humoral immune response (reviewed
Open Access
*Correspondence: marti.cortey@uab.cat
†Martí Cortey and Gaston Arocena contributed equally to this work 1 Departament de Sanitat i d’Anatomia Animals, Universitat Autònoma de
Barcelona, 08193 Cerdanyola Del Vallès, Spain
Page 2 of 6 Cortey et al. Vet Res (2018) 49:19
by [9]). Typically, PRRSv shows strong inhibitory effects on Type I interferons (IFN-β, IFN-α), affects the expres-sion of several interleukins (i.e. IL-1, IL-6, IL-8, IL-10, TNF-α) and down-regulates swine leucocyte class I (SLA-I) antigens [10]. Also, several pattern recognition toll-like receptors (TLR3, TLR7, TLR8 and TLR9) are involved in the interaction between PRRSv and the host immune system [11]. It is increasingly evident that dif-ferent strains may have a difdif-ferent potential for interfer-ing with the pig immune system [10, 12]. Besides, host’s genetic traits may influence the immune response after PRRSv vaccination [13], or the course of PRRSv infec-tion [14]. For instance, the risk of infection has been suggested to be related with several single nucleotide polymorphisms (SNPs) in CD163 and CD169 [15]. Also, other SNPs and microRNAs (miRs) especially in proteins involved in antiviral and inflammatory response have been associated to differential susceptibility to PRRSv infection [16–19].
In general, it is assumed that PRRSv only induces par-tial protection against heterologous strains [20] being impossible by now to forecast the degree of protection between two different isolates. In addition, large indi-vidual variation in the immune response is seen between individuals. For example, some individuals may show full or almost protection against a given isolate, while others are only partially protected or not protected at all [13].
The most widely admitted concept is that immunity against PRRSv is multigenic and may substantially vary between individuals. The aim of the present study was
to compare several genes that encode for molecules involved in the immune response between two groups of vaccinated pigs that experienced short or long viremic periods after PRRSv challenge. These analyses include the sequencing of four SLA Class I, two Class II allele groups, and CD163 (Table 1), plus the analysis by quan-titative realtime RT-PCR of the constitutive expression of TLR2, TLR3, TLR4, TLR7, TLR8 and TLR9 mRNA and other molecules in peripheral blood mononuclear cells (PBMC) (Table 2).
Animal experiment
Samples selected come from animals studied in a trans-mission by contact experiment of PRRSv-1 [21]. Briefly, commercial cross-breed pigs were vaccinated with a live modified commercial vaccine and challenged with the PRRSv-1 strain CReSA3267 (Accession Number JF276435) 30 days later. Animals were bled at several time points before and after challenge. The viral load was quantified in sera samples by means of one step RT-PCR (qRT-PCR) targeting PRRSv ORF7. According to the duration of the viremia, 20 pigs were chosen and classified for the purposes of the present study as short-viremic (namely less than 5 days of viremia after chal-lenge, SV, n = 8) or long-viremic (LV, ≥ 5 days of viremia,
n = 12). The spleens and PBMCs of the selected animals
collected at the end of the study (30 days post-challenge) were used for sequencing, TLR and cytokine expression analyses.
Table 1 SLA Class I and Class II, allele groups and CD163 analysed by sanger sequencing
Length of the PCR fragments amplified, number of contigs obtained (out of 20 analysed), mean coverage per position of the contigs obtained and primers used. a [27], b [28], c [29], d [16].
Allele Group/gene Amplicon size (in bp) Contigs obtained Mean coverage PCR primers
SLA Class I
SLA‑1*07a 220 9 2 SLA‑1*07XX F 5′‑GCCGGGTCTCACACCATCCAGAT‑3′
SLA‑1*07XX R 5′‑GGCCCTGCAGGTAGCTCCTCAAT‑3′
SLA‑1*08a 577 18 2 SLA‑1*08XX F 5′‑CGCGTGGACTCCCGCTTCTTCATT‑3′
SLA‑1*08XX R 5′‑CCAGGAGCGCAGGTCCTCGTT‑3′
SLA‑2*05a 544 19 2 SLA‑2*05XX F 5′‑CGAGTGAACCTGCGCACAGCTCTT‑3′
SLA‑2*05XX R 5′‑CTGCAGCGTGTCCTTCCCCATCTC‑3′
SLA‑3*04a 192 20 2 SLA‑3*04XX F 5′‑GGAAGCCCCGTTTCATCGAA‑3′
SLA‑3*04XX R 5′‑GCAGGTTTTTCAGGTTCACTCGGA‑3′ SLA Class II
SLA‑2*DQAb 898 20 3.38 DQAiF3 5′‑CTAGAGACTGTGCCACAGATGAAG‑3′
DQAe3R1 5′‑ACAGATGAGGGTGTTGGGCTGA‑3′
SLA‑2*DRBc 1308 12 2.51 DRBi1F9 5′‑GCGGTGCCTTCAGCCTTTTCAGGAG‑3′
DRBi2R9 5′‑AACAGTAGCAACTGTTTTGAGAGC‑3′
CD163d 3813 11 3.55 CD163‑Ex7Fw 5′‑ATTCTGACTTCTCTCTGGAGGC‑3′
Sanger sequencing
Table 1 depicts the host genes analysed and the prim-ers used. Total DNA from spleen samples was extracted using the DNeasy Blood & Tissue Kit (QIAGEN, Hilden, Germany). PCR products were amplified using the AccuPrime™ Pfx DNA polymerase (Fisher Scientific,
Hampton, USA) following the guidelines and the PCR conditions recommended by the supplier and the refer-ences provided. PCR products were sequenced using BigDye (Applied Biosystems, Foster City, USA) and chro-matograms were aligned with SeqMan v7 (DNASTAR, Madison, USA). Mean coverages of the final contigs ranged between 2 and 3.55 lectures per position. Dou-ble peak ambiguities in heterozygote individuals were assigned to individual alleles by comparing them with the chromatograms of the homozygote ones. Thus, for every studied animal and gene analysed two alleles were built up. The evolutionary relationships among alleles were analysed by means of a Neighbor-Joining (NJ) tree based on the pairwise distance matrix, calculated with the Tamura-Nei model. The confidence of the tree internal branches were calculated with 1000 bootstrap pseudo-replicates.
All trees, irrespective of being calculated from the four SLA-Class I allele groups, the two SLA-Class II, or the CD163 datasets, showed a mixed clustering of SV and LV animals. Figure 1 shows as an example the phyloge-netic trees obtained for the CD163 and the SLA-1*04 allele group. Moreover, in the present study, the three
CD163 SNPs associated with PRRSv risk infection by [15] did not showed differential results between SV and LV groups: for the SNP A2552G the combination AA, asso-ciated with lower infections risk, was present in all but one pig; the higher risk genotype for the SNP G2277A was not present in any of the studied pigs; and in the SNP C2700A the higher risk genotype AA was present in a single individual, the same that not harboured the lower risk AA genotype for the A2552G SNP.
qRT‑PCR
The constitutive levels of mRNA expression of differ-ent TLRs, TNF-α and IFN-γ were analysed in PBMCs (Table 2). Total RNA was extracted using Trizol (Invitro-gen, Paisley, UK) according to the manufacturer’s instruc-tions. To reduce DNA contamination, DNase digestion was conducted, followed with a further purification step using the RNeasy miniki (Qiagen, Crawley, UK). RNA samples were processed by a qRT-PCR one step (Brilliant III Ultra-Fast SYBR Green QRT-PCR Master Mix, Agilent technologies) with a Stratagene MX3000P (Stratagene, La Jolla, CA, USA). Samples were tested in triplicate, B-actin served as the housekeeping gene and results were calculated as described previously [22]. Before comparing groups all Ct values were normalized with the corresponding values of the housekeeping gene. Figure 2 shows the mean and SD cycle threshold number as a measure of the mRNA expression. Significant dif-ferences between groups were observed for TNF-α and
Table 2 Genes analysed by RT-qPCR. Length of the PCR fragments amplified, and primers used
a [30].
Gene Ensemble gene Amplicon size (bp) PCR primers
TLRs TLR2a ENSSSCG00000009002 162 TLR2‑F 5′‑TCACTTGTCTAACTTATCATCCTCTTG‑3′ TLR2‑R 5′‑TCAGCGAAGGTGTCATTATTGC‑3′ TLR3a ENSSSCG00000015801 112 TLR3‑F 5′‑AGTAAATGAATCACCCTGCCTAGCA‑3′ TLR3‑R 5′‑GCCGTTGACAAAACACATAAGGACT‑3′ TLR4a ENSSSCG00000005503 108 TLR4‑F 5′‑GCCATCGCTGCTAACATCATC‑3′ TLR4‑R 5′‑CTCATACTCAAAGATACACCATCGG‑3′ TLR5a Gene ID 100144476 156 TLR5‑F 5′‑CTCGCCCACCACATTA‑3′ TLR5‑R 5′‑TGAGGGTCCCAAAGAGT‑3′ TLR7a ENSSSCT00000035232.2 TLR7‑F 5′‑GGGAAAGCTCCAGTATCTGC‑3′ TLR7‑R 5′‑TGAGGCTTCTGGAACAGTTG‑3′ TLR8a ENSSSCG00000012118 105 TLR8‑F 5′‑AAGACCACCACCAACTTAGCC‑3′ TLR8‑R 5′‑GACCCTCAGATTCTCATCCATCC‑3′ TLR9a ENSSSCG00000011436 122 TLR9‑F 5′‑CACGACAGCCGAATAGCAC‑3′ TLR9‑R 5′‑GGGAACAGGGAGCAGAGC‑3′ TNF‑αa ENSSSCG00000001404 102 TNF‑α‑F 5′‑TGGTGGTGCCGACAGATGG‑3′
IFN‑γa ENSSSCT00000055560.1 132 TNFG‑F‑5′‑CTGGGAAACTGAATGACTTCG‑3′
Page 4 of 6 Cortey et al. Vet Res (2018) 49:19
Figure 1 Phylogenetic trees. (A) NJ tree based on the 3813 bp of the CD163 analysed, corresponding to the exons 7–11 of the gene; (B) NJ tree
based on the 641 bp of the SLA‑1*04. Only bootstrap values higher than 65 were shown. Sequence labels include the pig identifier, the allele and the days of viremia.
Figure 2 qRT-PCR mRNA quantification. Statistical differences in the cycle number of qRT‑PCR amplification (CTs) of different Toll‑like receptors
TLR2 (p < 0.05); while a trend was observed for TLR8 and TLR9 (p = 0.06). In all these cases, the mean Ct val-ues observed for the SV group were higher compared to the LV group, indicating a lower mRNA expression in pigs with shorter viremic periods.
Discussion
The available literature about the genetics of host response to PRRSv show that several genes are involved in differential responses against the infection. Signifi-cant variation exists for a number of immune traits that at least include: antibody response, proliferative and cytokine responses of mononuclear cells, delayed-type hypersensitivity reactions, leukocyte number, and differ-ential white blood cell counts (reviewed in [23]). Indeed, intrinsic immune differences have been reported among pig breeds [18, 22, 23], within herds [13] and even among tissues within an individual.
The results obtained in this study indicate a lack of correlation between the length and titre of the viremia, in vaccinated pigs and the clustering of the sequences of CD163, four SLA class I and two SLA class II allele groups (Figure 1). However, it should be noted that the low number of SLA allele groups analysed in the present study may certainly underrepresent the existing diversity. One of the most remarkable features of the SLA region is the extremely high degree of genetic polymorphism. More than a hundred allele groups have been defined for both SLA I (129) and SLA II (167); each of which present several alleles. For instance, 44 alleles have been described among the 12 SLA-1 allele groups; while, the 14 DRB1 allele groups present a total of 82 alleles [24]. Similarly, the amount of nucleotide diversity detected for the CD163 dataset (34 variable positions along the 3813 bp analysed) was not correlated with the length of the viremia (Figure 1). Also, none of the CD163 SNPs associated to PRRSv risk infection [15] were differentially expressed between SV and LV animals. Recent results from CD163 knockout pigs [25] indicate the complete absence of PRRSv-1 infection in PAMs and a substan-tial reduction in PRRSv-2, suggesting the pivotal role of CD163 in PRRSv-1 infection that may not be neces-sarily related with the length of the viremia. Finally, the constitutive mRNA expression levels of most analysed TLR genes in PBMC did not report significant differences with the exception of TLR2 and TNF-α expression (Fig-ure 2). Interestingly, PBMCs of pigs with SV presented a lower constitutive mRNA levels of TNF-α and TLR2 than pigs with LV. This finding is noteworthy as it could indicate that a more limited inflammatory response may be operating in these pigs since exacerbated inflamma-tory responses in PRRSV-infected pigs have been corre-lated with more persistent infections and a worse clinical
resolution [26]. Generally speaking, the results does not support, for the genes examined, the existence of a clear allele combination or host genetic profile that can be correlated with the length of the viremia in vaccinated animals.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
MC, GA, AV and YL performed the sequencing lab work; TAA, LD, ADW and ALA did the qRT‑PCR lab work; MC, GA, GMV, LD, TAA and EM analysed the data, discussed the results and wrote the manuscript. All authors read and approved the final manuscript.
Acknowledgements
M Cortey was funded by the Spanish Ministry of Economy and Competitive‑ ness (project AGL2014‑61204‑JIN). L Darwich was granted by the Spanish Ministry of Education, Culture and Sports (Grant Code CAS14/00139). AL Archibald, AD Wilson and T Ait‑Ali acknowledge support from BBSRC Institute Strategic Programme Grants (BB/J004227/1, BB/P013740/1).
Ethics statement
The animal sera and tissue samples analysed were re‑used from a former pro‑ ject (RTA2011/000119), where EU and national legislation on ethics in research were strictly met.
Author details
1 Departament de Sanitat i d’Anatomia Animals, Universitat Autònoma de
Barcelona, 08193 Cerdanyola Del Vallès, Spain. 2 The Roslin Institute and Royal
(Dick) School of Veterinary Studies, University of Edinburgh, Midlothian EH25 9RG, UK. 3 IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA‑UAB),
Campus de la Universitat Autònoma de Barcelona, 08193 Cerdanyola Del Vallès, Spain.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in pub‑ lished maps and institutional affiliations.
Received: 13 December 2017 Accepted: 8 February 2018
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